LATERAL BRANCHING OXIDOREDUCTASE acts in the final stages of strigolactone biosynthesis in Arabidopsis.

Strigolactones are a group of plant compounds of diverse but related chemical structures. They have similar bioactivity across a broad range of plant species, act to optimize plant growth and development, and promote soil microbe interactions. Carlactone, a common precursor to strigolactones, is produced by conserved enzymes found in a number of diverse species. Versions of the MORE AXILLARY GROWTH1 (MAX1) cytochrome P450 from rice and Arabidopsis thaliana make specific subsets of strigolactones from carlactone. However, the diversity of natural strigolactones suggests that additional enzymes are involved and remain to be discovered. Here, we use an innovative method that has revealed a missing enzyme involved in strigolactone metabolism. By using a transcriptomics approach involving a range of treatments that modify strigolactone biosynthesis gene expression coupled with reverse genetics, we identified LATERAL BRANCHING OXIDOREDUCTASE (LBO), a gene encoding an oxidoreductase-like enzyme of the 2-oxoglutarate and Fe(II)-dependent dioxygenase superfamily. Arabidopsis lbo mutants exhibited increased shoot branching, but the lbo mutation did not enhance the max mutant phenotype. Grafting indicated that LBO is required for a graft-transmissible signal that, in turn, requires a product of MAX1. Mutant lbo backgrounds showed reduced responses to carlactone, the substrate of MAX1, and methyl carlactonoate (MeCLA), a product downstream of MAX1. Furthermore, lbo mutants contained increased amounts of these compounds, and the LBO protein specifically converts MeCLA to an unidentified strigolactone-like compound. Thus, LBO function may be important in the later steps of strigolactone biosynthesis to inhibit shoot branching in Arabidopsis and other seed plants.

Analysis of central Hox protein types across bilaterian clades: on the diversification of central Hox proteins from an Antennapedia/Hox7-like protein.

Hox proteins are among the most intensively studied transcription factors and represent key factors in establishing morphological differences along the anterior-posterior axis of animals. They are generally regarded as highly conserved in function, a view predominantly based on experiments comparing a few (anterior) Hox proteins. However, the extent to which central or abdominal Hox proteins share conserved functions and sequence signatures remains largely unexplored. To shed light on the functional divergence of the central Hox proteins, we present an easy to use resource aimed at predicting the functional similarities of central Hox proteins using sequence elements known to be relevant to Hox protein functions. We provide this resource both as a stand-alone download, including all information, as well as via a simplified web-interface that facilitates an accurate and fine-tuned annotation of novel Hox sequences. The method used in the manuscript is, so far, the only published sequence-based method capable of differentiating between the functionally distinct central Hox proteins with near-identical homeodomains (such as the Drosophila Antp, Ubx and Abd-A Hox proteins). In this manuscript, a pairwise-sequence-similarity based approach (using the bioinformatics tool CLANS) is used to analyze all available central Hox protein sequences. The results are combined with a large-scale species phylogeny to depict the presence/absence of central Hox sequence-types across the bilaterian lineage. The obtained pattern of distribution of the Hox sequence-types throughout the species tree enables us to infer at which branching point a specific type of central Hox protein was present. Based on the Hox sequences currently available in public databases, seven sequence-similarity groups could be identified for the central Hox proteins, two of which have never been described before (Echi/Hemi7 and Echi/Hemi8). Our work also shows, for the first time, that Antp/Hox7-like sequences are present throughout all bilaterian clades and that all other central Hox protein groups are specific to sub-lineages in the protostome or deuterostome branches only.

microRNA profiling of root tissues and root forming explant cultures in Medicago truncatula.

Plant root architecture is regulated by the initiation and modulation of cell division in regions containing pluripotent stem cells known as meristems. In roots, meristems are formed early in embryogenesis, in the case of the root apical meristem (RAM), and during organogenesis at the site of lateral root or, in legumes, nodule formation. Root meristems can also be generated in vitro from leaf explants cultures supplemented with auxin. microRNAs (miRNAs) have emerged as regulators of many key biological functions in plants including root development. To identify key miRNAs involved in root meristem formation in Medicago truncatula, we used deep sequencing to compare miRNA populations. Comparisons were made between: (1) the root tip (RT), containing the RAM and the elongation zone (EZ) tissue and (2) root forming callus (RFC) and non-root forming callus (NRFC). We identified 83 previously reported miRNAs, 24 new to M. truncatula, in 44 families. For the first time in M. truncatula, members of conserved miRNA families miR165, miR181 and miR397 were found. Bioinformatic analysis identified 38 potential novel miRNAs. Selected miRNAs and targets were validated using Taqman miRNA assays and 5' RACE. Many miRNAs were differentially expressed between tissues, particularly RFC and NRFC. Target prediction revealed a number of miRNAs to target genes previously shown to be differentially expressed between RT and EZ or RFC and NRFC and important in root development. Additionally, we predict the miRNA/target relationships for miR397 and miR160 to be conserved in M. truncatula. Amongst the predictions, were AUXIN RESPONSE FACTOR 10, targeted by miR160 and a LACCASE-like gene, targeted by miR397, both are miRNA/target pairings conserved in other species.

Comparative proteomic profiles of the soybean (Glycine max) root apex and differentiated root zone.

The root apical meristem (RAM) is responsible for the growth of the plant root system. Because of the importance of root architecture in the performance of crop plants, we established a proteome reference map of the soybean root apex and compared this with the proteome of the differentiated root zone. The root apex samples contained the apical 1 mm of the root, comprising the RAM, quiescent center and root cap. We identified 342 protein spots from 550 excised proteins (∼62%) of root apex samples by MALDI-TOF MS/MS analysis. All these proteins were also present in the differentiated root, but differed in abundance. Functional classification showed that the most numerous protein categories represented in the root were those of stress response, glycolysis, redox homeostasis and protein processing. Using DIGE, we identified 73 differentially accumulated proteins between root apex and differentiated root. Proteins overrepresented in the root apex belonged primarily to the pathways for protein synthesis and processing, cell redox homeostasis and flavonoid biosynthesis. Proteins underrepresented in the root apex were those of glycolysis, tricarboxylic acid metabolism and stress response. Our results highlight the importance of stress and defense response, redox control and flavonoid metabolism in the root apex.

PathExpress update: the enzyme neighbourhood method of associating gene-expression data with metabolic pathways.

The post-genomic era presents us with the challenge of linking the vast amount of raw data obtained with transcriptomic and proteomic techniques to relevant biological pathways. We present an update of PathExpress, a web-based tool to interpret gene-expression data and explore the metabolic network without being restricted to predefined pathways. We define the Enzyme Neighbourhood (EN) as a sub-network of linked enzymes with a limited path length to identify the most relevant sub-networks affected in gene-expression experiments. PathExpress is freely available at: http://bioinfoserver.rsbs.anu.edu.au/utils/PathExpress/.

Global changes in the transcript and metabolic profiles during symbiotic nitrogen fixation in phosphorus-stressed common bean plants.

Phosphorus (P) deficiency is widespread in regions where the common bean (Phaseolus vulgaris), the most important legume for human consumption, is produced, and it is perhaps the factor that most limits nitrogen fixation. Global gene expression and metabolome approaches were used to investigate the responses of nodules from common bean plants inoculated with Rhizobium tropici CIAT899 grown under P-deficient and P-sufficient conditions. P-deficient inoculated plants showed drastic reduction in nodulation and nitrogenase activity as determined by acetylene reduction assay. Nodule transcript profiling was performed through hybridization of nylon filter arrays spotted with cDNAs, approximately 4,000 unigene set, from the nodule and P-deficient root library. A total of 459 genes, representing different biological processes according to updated annotation using the UniProt Knowledgebase database, showed significant differential expression in response to P: 59% of these were induced in P-deficient nodules. The expression platform for transcription factor genes based in quantitative reverse transcriptase-polymerase chain reaction revealed that 37 transcription factor genes were differentially expressed in P-deficient nodules and only one gene was repressed. Data from nontargeted metabolic profiles indicated that amino acids and other nitrogen metabolites were decreased, while organic and polyhydroxy acids were accumulated, in P-deficient nodules. Bioinformatics analyses using MapMan and PathExpress software tools, customized to common bean, were utilized for the analysis of global changes in gene expression that affected overall metabolism. Glycolysis and glycerolipid metabolism, and starch and Suc metabolism, were identified among the pathways significantly induced or repressed in P-deficient nodules, respectively.

A gene expression atlas of the model legume Medicago truncatula.

Legumes played central roles in the development of agriculture and civilization, and today account for approximately one-third of the world's primary crop production. Unfortunately, most cultivated legumes are poor model systems for genomic research. Therefore, Medicago truncatula, which has a relatively small diploid genome, has been adopted as a model species for legume genomics. To enhance its value as a model, we have generated a gene expression atlas that provides a global view of gene expression in all major organ systems of this species, with special emphasis on nodule and seed development. The atlas reveals massive differences in gene expression between organs that are accompanied by changes in the expression of key regulatory genes, such as transcription factor genes, which presumably orchestrate genetic reprogramming during development and differentiation. Interestingly, many legume-specific genes are preferentially expressed in nitrogen-fixing nodules, indicating that evolution endowed them with special roles in this unique and important organ. Comparative transcriptome analysis of Medicago versus Arabidopsis revealed significant divergence in developmental expression profiles of orthologous genes, which indicates that phylogenetic analysis alone is insufficient to predict the function of orthologs in different species. The data presented here represent an unparalleled resource for legume functional genomics, which will accelerate discoveries in legume biology.

PathExpress: a web-based tool to identify relevant pathways in gene expression data.

PathExpress is a web-based tool developed to interpret gene expression data obtained from microarray experiments by identifying the most relevant metabolic pathways associated with a subset of genes (e.g. differentially expressed genes). A graphical pathway representation permits the visualization of the expressed genes in a functional context. Based on the publicly accessible KEGG Ligand database, PathExpress can be adapted to any organism and is currently available for seven Affymetrix genome arrays. About 20% of the probe sets of each array have been assigned to Enzyme Commission numbers by homology relationship and linked to corresponding metabolic pathways. PathExpress is available at http://bioinfoserver.rsbs.anu.edu.au/utils/PathExpress/.

Transcriptional profiling of Medicago truncatula meristematic root cells.

BACKGROUND: The root apical meristem of crop and model legume Medicago truncatula is a significantly different stem cell system to that of the widely studied model plant species Arabidopsis thaliana. In this study we used the Affymetrix Medicago GeneChip(R) to compare the transcriptomes of meristem and non-meristematic root to identify root meristem specific candidate genes. RESULTS: Using mRNA from root meristem and non-meristem we were able to identify 324 and 363 transcripts differentially expressed from the two regions. With bioinformatics tools developed to functionally annotate the Medicago genome array we could identify significant changes in metabolism, signalling and the differentially expression of 55 transcription factors in meristematic and non-meristematic roots. CONCLUSION: This is the first comprehensive analysis of M. truncatula root meristem cells using this genome array. This data will facilitate the mapping of regulatory and metabolic networks involved in the open root meristem of M. truncatula and provides candidates for functional analysis.

Bioinformatic analysis of the CLE signaling peptide family.

BACKGROUND: Plants encode a large number of leucine-rich repeat receptor-like kinases. Legumes encode several LRR-RLK linked to the process of root nodule formation, the ligands of which are unknown. To identify ligands for these receptors, we used a combination of profile hidden Markov models and position-specific iterative BLAST, allowing us to detect new members of the CLV3/ESR (CLE) protein family from publicly available sequence databases. RESULTS: We identified 114 new members of the CLE protein family from various plant species, as well as five protein sequences containing multiple CLE domains. We were able to cluster the CLE domain proteins into 13 distinct groups based on their pairwise similarities in the primary CLE motif. In addition, we identified secondary motifs that coincide with our sequence clusters. The groupings based on the CLE motifs correlate with known biological functions of CLE signaling peptides and are analogous to groupings based on phylogenetic analysis and ectopic overexpression studies. We tested the biological function of two of the predicted CLE signaling peptides in the legume Medicago truncatula. These peptides inhibit the activity of the root apical and lateral root meristems in a manner consistent with our functional predictions based on other CLE signaling peptides clustering in the same groups. CONCLUSION: Our analysis provides an identification and classification of a large number of novel potential CLE signaling peptides. The additional motifs we found could lead to future discovery of recognition sites for processing peptidases as well as predictions for receptor binding specificity.

Mclip: motif detection based on cliques of gapped local profile-to-profile alignments.

UNLABELLED: A multitude of motif-finding tools have been published, which can generally be assigned to one of three classes: expectation-maximization, Gibbs-sampling or enumeration. Irrespective of this grouping, most motif detection tools only take into account similarities across ungapped sequence regions, possibly causing short motifs located peripherally and in varying distance to a 'core' motif to be missed. We present a new method, adding to the set of expectation-maximization approaches, that permits the use of gapped alignments for motif elucidation. AVAILABILITY: The program is available for download from: http://bioinfoserver.rsbs.anu.edu.au/downloads/mclip.jar. SUPPLEMENTARY INFORMATION: http://bioinfoserver.rsbs.anu.edu.au/utils/mclip/info.php.

Analyzing microarray data using CLANS.

UNLABELLED: Analysis of microarray experiments is complicated by the huge amount of data involved. Searching for groups of co-expressed genes is akin to searching for protein families in a database as, in both cases, small subsets of genes with similar features are to be found within vast quantities of data. CLANS was originally developed to find protein families in large sets of amino acid sequences where the amount of data involved made phylogenetic approaches overly cumbersome. We present a number of improvements that greatly extend the previous version of CLANS and show its application to microarray data as well as its ability of incorporating additional information to facilitate interactive analysis. AVAILABILITY: The program is available for download from: http://bioinfoserver.rsbs.anu.edu.au/downloads/clans/

Detecting genetic recombination.

Recombination is the major motor of evolution. While mutations result in gradual changes, recombination reshuffles entire functional modules and thus progresses evolution in leaps and bounds. We need to identify recombination breakpoints in sequences to understand the evolutionary process, the impact of recombination, and to reconstruct the phylogenetic history of genes and genomes. This chapter provides a step by step guide for detecting recombination even in large and complex sequence alignments.

Identifying components of complexes.

Identifying and analyzing components of complexes is essential to understand the activities and organization of the cell. Moreover, it provides additional information on the possible function of proteins involved in these complexes. Two bioinformatics approaches are usually used for this purpose. The first is based on the identification, by clustering algorithms, of full or densely connected sub-graphs in protein-protein interaction networks derived from experimental sources that might represent complexes. The second approach consists of the integration of genomic and proteomic data by using Bayesian networks or decision trees. This approach is based on the hypothesis that proteins involved in a complex usually share common properties.

GeneBins: a database for classifying gene expression data, with application to plant genome arrays.

BACKGROUND: To interpret microarray experiments, several ontological analysis tools have been developed. However, current tools are limited to specific organisms. RESULTS: We developed a bioinformatics system to assign the probe set sequences of any organism to a hierarchical functional classification modelled on KEGG ontology. The GeneBins database currently supports the functional classification of expression data from four Affymetrix arrays; Arabidopsis thaliana, Oryza sativa, Glycine max and Medicago truncatula. An online analysis tool to identify relevant functions is also provided. CONCLUSION: GeneBins provides resources to interpret gene expression results from microarray experiments. It is available at http://bioinfoserver.rsbs.anu.edu.au/utils/GeneBins/

Computational analyses show A-to-G mutations correlate with nascent mRNA hairpins at somatic hypermutation hotspots.

Activation-induced cytidine deaminase (AID) initiates Phase I somatic hypermutation (SHM) of antibody genes by deaminating deoxy-cytosine to deoxy-uracil (C-to-U). These lesions trigger Phase II, a poorly understood process of error-prone repair targeting A-T pairs by DNA polymerase eta (Pol eta). Since Pol eta is also a reverse transcriptase, Phase II could involve copying off RNA as well as DNA templates. We explore this idea further since in an RNA-based pathway it is conceivable that adenosine-to-inosine (A-to-I) RNA editing causes A-to-G transitions since I like G pairs with C. Adenosine deaminases (ADARs) are known to preferentially edit A nucleotides that are preceded by an A or U (W) in double-stranded RNA substrates. On this assumption and using a theoretical bioinformatics approach we show that a significant and specific correlation (P<0.002) exists between the frequency of WA-to-WG mutations and the number of mRNA hairpins that could potentially form at the mutation site. This implies roles for both RNA editing and reverse transcription during SHM in vivo and suggests definitive genetic experiments targeting the appropriate ADAR1 isoform (gammaINF-ADAR1) and/or Ig pre-mRNA templates.

Extending MapMan: application to legume genome arrays.

MOTIVATION: Based on a gene classification into hierarchical categories ('BINs'), MapMan was originally developed to display Arabidopsis thaliana gene expression in a functional context. We have created a bioinformatics system to extend MapMan to any organism by using a new BIN structure based on the KEGG database. Gene sequences are assigned to this ontology by homology relationships in four reference databases: KEGG, COG, Swiss-Prot and Gene Ontology. We applied this system to tailor MapMan to the GeneChips of two model legumes, Glycine max and Medicago truncatula. We also developed a module to identify the most relevant pathways involved. AVAILABILITY: All mapping files, pathway pictures and the analysis method are available at http://bioinfoserver.rsbs.anu.edu.au/

Corrigendum to "Plant MicroRNA Prediction by Supervised Machine Learning Using C5.0 Decision Trees".

[This corrects the article DOI: 10.1155/2012/652979.].

A global analysis of protein expression profiles in Sinorhizobium meliloti: discovery of new genes for nodule occupancy and stress adaptation.

A proteomic examination of Sinorhizobium meliloti strain 1021 was undertaken using a combination of 2-D gel electrophoresis, peptide mass fingerprinting, and bioinformatics. Our goal was to identify (i) putative symbiosis- or nutrient-stress-specific proteins, (ii) the biochemical pathways active under different conditions, (iii) potential new genes, and (iv) the extent of posttranslational modifications of S. meliloti proteins. In total, we identified the protein products of 810 genes (13.1% of the genome's coding capacity). The 810 genes generated 1,180 gene products, with chromosomal genes accounting for 78% of the gene products identified (18.8% of the chromosome's coding capacity). The activity of 53 metabolic pathways was inferred from bioinformatic analysis of proteins with assigned Enzyme Commission numbers. Of the remaining proteins that did not encode enzymes, ABC-type transporters composed 12.7% and regulatory proteins 3.4% of the total. Proteins with up to seven transmembrane domains were identified in membrane preparations. A total of 27 putative nodule-specific proteins and 35 nutrient-stress-specific proteins were identified and used as a basis to define genes and describe processes occurring in S. meliloti cells in nodules and under stress. Several nodule proteins from the plant host were present in the nodule bacteria preparations. We also identified seven potentially novel proteins not predicted from the DNA sequence. Post-translational modifications such as N-terminal processing could be inferred from the data. The posttranslational addition of UMP to the key regulator of nitrogen metabolism, PII, was demonstrated. This work demonstrates the utility of combining mass spectrometry with protein arraying or separation techniques to identify candidate genes involved in important biological processes and niche occupations that may be intransigent to other methods of gene expression profiling.